MeLOn
Write_GP_to_json.m File Reference

Functions

 json_X (end)
 
 fwrite (fid, json)
 
 fclose (fid)
 

Variables

 sample_lb = min(X)
 
Compute lower bound of input data sample_ub = max(X)
 
Compute upper bound of input data [nX, DX] = size(X)
 
scale hyperparameters from log ell = exp(Opt.GP.hyp.cov(1:DX))
 
 sf2 = exp(2*Opt.GP.hyp.cov(DX+1))
 
data nY = nY
 
data DX = DX
 
data DY = DY
 
data matern = Opt.GP.matern
 
data meanfunction = 0
 
data meanOfOutput = meanOfOutput
 
data stdOfOutput = stdOfOutput
 
data inputLowerBound = {sample_lb}
 
data inputUpperBound = {sample_ub}
 
data problemLowerBound = {lb}
 
data problemUpperBound = {ub}
 
fix for column vector data X = {'X_dummy'}
 
 json_X = sprintf('[%f],',xScaled)
 
end data Y = yScaled
 
data K = Opt.GP.K
 
data invK = Opt.GP.invK
 
 json = jsonencode(data)
 
end fid = fopen(filename, 'w')
 
 path = fullfile(pwd, filename)
 

Function Documentation

◆ fclose()

fclose ( fid  )

◆ fwrite()

fwrite ( fid  ,
json   
)

◆ json_X()

json_X ( end  )

Variable Documentation

◆ data

scale data = size(X)

◆ DX

if DX = DX

◆ DY

data DY = DY

◆ ell

else data ell = exp(Opt.GP.hyp.cov(1:DX))

◆ fid

end fid = fopen(filename, 'w')

◆ inputLowerBound

data inputLowerBound = {sample_lb}

◆ inputUpperBound

data inputUpperBound = {sample_ub}

◆ invK

data invK = Opt.GP.invK

◆ json

json = jsonencode(data)

◆ json_X

json_X = sprintf('[%f],',xScaled)

◆ K

data K = Opt.GP.K

◆ matern

data matern = Opt.GP.matern

◆ meanfunction

data meanfunction = 0

◆ meanOfOutput

data meanOfOutput = meanOfOutput

◆ nY

data nY = nY

◆ path

path = fullfile(pwd, filename)

◆ problemLowerBound

data problemLowerBound = {lb}

◆ problemUpperBound

data problemUpperBound = {ub}

◆ sample_lb

sample_lb = min(X)

◆ sample_ub

Compute lower bound of input data sample_ub = max(X)

◆ sf2

data sf2 = exp(2*Opt.GP.hyp.cov(DX+1))

◆ stdOfOutput

data stdOfOutput = stdOfOutput

◆ X

data X = {'X_dummy'}

◆ Y

end data Y = yScaled